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Dataset results
27 results for “penalties”
Energy-Dependent, Self-Adaptive Mesh h(p)-Refinement of an Interior-Penalty Scheme for a Discontinuous Galerkin Isogeometric Analysis Spatial Discretisation of the Multi-Group Neutron Diffusion Equation with Dual-Weighted Residual Error Measures
<p>This repository holds all of the raw data generated by my (Modern) Fortran code for a paper "Energy-Dependent, Self-Adaptive Mesh h(p)-Refinement of an Interior-Penalty Scheme for a Discontinuous Galerkin Isogeometric Analysis Spatial Discretisation of the Multi-Group Neutron Diffusion Equation with Dual-Weighted Residual Error Measures".</p><p>The (Modern) Fortran code solves the multi-group neutron diffusion equation using a novel IGA-based spatial discretisations.</p>
Dataset for meta-analysis "The motherhood penalty's size and factors"
<p><strong>PLEASE, CITE AS Kalabikhina IE, Kuznetsova PO, Zhuravleva SA (2024) Size and factors of the motherhood penalty in the labour market: A meta-analysis. Population and Economics 8(2): 178-205. <a href="https://doi.org/10.3897/popecon.8.e121438" target="_blank" rel="noopener">https://doi.org/10.3897/popecon.8.e121438</a></strong></p> <p> </p> <p><strong>Explanatory note 1: List of papers used in the meta-analysis - see the file "Meta_regression_analysis_papers".</strong></p> <p><strong>The data is presented in WORD format.</strong></p> <p> </p> <p><strong>Explanatory note 2: Set of data used in the meta-analysis - see the file "Meta_regression_analysis_table".</strong></p> <p><strong>The data is presented in EXCEL format. </strong></p> <p><strong>Description of table headers:</strong></p> <p>estimate_number - Number of the estimate</p> <p>paper_number - Number of the paper</p> <p>paper_name - Paper (year and first author)</p> <p>paper_excluded - Paper was excluded from the final sample</p> <p>survey - Data source</p> <p>table_in_paper - Number of the table with the regression results in the paper</p> <p>coeff - Regression coefficient for parenthood variable (estimate)</p> <p>se - SE of the estimate</p> <p>t - t-value of the estimate</p> <p>ols - Estimate is obtained using the OLS method</p> <p>fixed_effects ­- Estimate is obtained using the fixed effects method</p> <p>panel - Model considers panel data (for several years)</p> <p>quintile - Estimate is obtained using the quintile regression method</p> <p>other - Estimate is obtained using other methods</p> <p>selection_into_motherhood - Estimate is obtained allowing for selection into motherhood</p> <p>hackman - Estimate is obtained allowing for selection into employment (Heckman procedure)</p> <p>annual_earnings - Annual earnings are considered in the model</p> <p>monthly_wage - Monthly wage is considered in the model</p> <p>daily_wage - Daily wage is considered in the model</p> <p>hourly_wage - Hourly wage is considered in the model</p> <p>min_age_kid - Child's age (minimum)</p> <p>max_age_kid - Child's age (maximum)</p> <p>motherhood - Model uses a dummy variable of the presence of children</p> <p>num_kids - Model uses a variable of the number of children</p> <p>kid1 - Model uses a variable of the presence of one child</p> <p>kid2p - Model uses a variable of the presence of two or more children</p> <p>kid2 - Model uses a variable of the presence of two children</p> <p>kid3p - Model uses a variable of the presence of three or more children</p> <p>kid3 - Model uses a variable of the presence of three children</p> <p>kid4p - Model uses a variable of the presence of three or more children</p> <p>race/nationality - Model includes a race/ethnicity variable</p> <p>age - Model includes the age variable</p> <p>marstat - Model includes the marital status variable</p> <p>oth_char_hh - Model includes any other variables of other household characteristics</p> <p>settl_type - Model includes a variable of the type of settlement (urban, rural)</p> <p>region - Model includes a variable of the region of the country</p> <p>education - Model includes information on the level of education</p> <p>experience - Model includes a variable of work experience</p> <p>pot_experience - Model includes a variable of potential work experience, to be calculated from the data on age and number of years of education</p> <p>tenure - Model includes a variable of the duration of employment at the current job</p> <p>interruptions - Model includes a variable of employment interruptions (related to motherhood)</p> <p>occupation - Model includes an occupation variable</p> <p>industry - Model includes a variable of the industry of employment</p> <p>union - Model includes a variable of trade union membership</p> <p>friendly_conditions - Model includes a variable of the favourable working conditions for mothers (flexible schedule, possibility to work from home, etc.).</p> <p>hours - Model includes a variable of the number of hours worked</p> <p>sector - Model includes a variable of the type of employer ownership (public or private)</p> <p>informal - Model includes a variable of informal employment</p> <p>size_ent - Model includes a variable of the employer size</p> <p>min_age_woman - Woman's age (minimum)</p> <p>max_age_woman - Woman's age (maximum)</p> <p>mean_age_woman - Woman's age (mean)</p> <p>restricted - Sample is limited</p> <p>private - Model considers only private sector employees</p> <p>state - Model considers only public sector employees</p> <p>full_time - Model considers only full-time workers</p> <p>part_time - Model considers only part-time workers</p> <p>better_educated - Model considers only women with a high level of education</p> <p>lower_educated - Model considers only women with a low level of education</p> <p>married - Model includes only married women</p> <p>single - Model includes only single women</p> <p>natives - Model includes only native women (born in the country)</p> <p>immigrants - Model includes only immigrant women (born abroad)</p> <p>race - Model includes only women of a particular race</p> <p>min_year - Time period (minimum year)</p> <p>max_year - Time period (maximum year)</p> <p>journal - Type of publication</p> <p>usa - Sample includes women from the USA</p> <p>western_europe - Sample includes women from Western Europe (Belgium, France, Germany, Luxembourg, the Netherlands, Switzerland)</p> <p>north_europe - Sample includes women from Northern Europe (Denmark, Finland, Norway, Sweden)</p> <p>south_europe - Sample includes women from Southern Europe (Greece, Italy, Portugal, Spain)</p> <p>east_centre_europe - Sample includes women from Central or Eastern Europe (Czechia, Hungary, Poland, Russia, Serbia, Ukraine)</p> <p>china - Sample includes women from China</p> <p>Russia - Sample includes women from Russia</p> <p>others - Sample includes women from other countries</p> <p>country - Country name</p>
On the conversion of CO2 to value added products over composite PdZn and H-ZSM-5 catalysts: excess Zn over Pd, a compromise or a penalty? Supplementary information
<p>Supplementary Material: N2 adsorption, TEM, XAS, PXRD, test results</p>
Results for paper "Optimal trace inequality constants for interior penalty discontinuous Galerkin discretisations of elliptic operators using arbitrary elements with non-constant Jacobians"
<p>Results for paper "Optimal trace inequality constants for interior penalty discontinuous Galerkin discretisations of elliptic operators using arbitrary elements with non-constant Jacobians"</p>
An Interior-Penalty Scheme for a Discontinuous Galerkin Isogeometric Analysis Spatial Discretization of the Self-Adjoint Angular Flux Form of the Multi-Group Neutron Transport Equation
<p>This repository holds all of the raw data generated by my (Modern) Fortran code for a paper "An Interior-Penalty Scheme for a Discontinuous Galerkin Isogeometric Analysis Spatial Discretization of the Self-Adjoint Angular Flux Form of the Multi-Group Neutron Transport Equation".</p> <p>The (Modern) Fortran code solves the SAAF form of the multi-group neutron transport equation using novel NURBS-based, IGA spatial discretisations.</p>
No risk – no fun: Penalty and recovery from spring frost damages in deciduous temperate trees
<p>Phenological shifts in response to changing climatic conditions are a key acclimation process for the persistence of perennial plants in temperate and boreal climates. The optimal time to leaf-out is the result of evolutionary processes determined by the trade-off between minimizing the risk of freezing damages and herbivory pressure while maximizing resource uptake to increase competitiveness against the other plants.</p> <p>We quantified the penalty exerted by frost exposure at the time of leaf emergence on plant development (reduction in leaf area, canopy duration, and growth) over the potential gains without frost (increased biomass and non-structural carbohydrate reserves), depending on when leaf-out occurs. To this purpose, we exposed 960 saplings of four temperate deciduous tree species with contrasting cold hardiness to two frost intensities shortly after leaf emergence, which was artificially induced at four occasions to reflect the whole range of natural leaf-out dates.</p> <p>One year above-ground biomass (AGB) increments following the frost revealed a clear ranking among the species depending on their strategy to cope with damaging frosts. Prunus avium (-41% of AGB-increment compared to control saplings) resprouted from the stem base, Quercus robur (-62%) rapidly produced new leaves from dormant reserve buds, Fagus sylvatica (-98%) showed the highest chlorophyll content in autumn and delayed senescence together with Carpinus betulus (-105%), which overcompensated NSC reserves after the growing season but showed highest mortality (up to 32%). In all species, NSC reserves recovered rapidly their initial stage at the expense of growth.</p> <p>The timing of leaf-out (advanced and delayed artificially) significantly affected the performance and recovery (regreening and growth) of both frozen and non-frozen saplings, with the lowest performance found at the most delayed leaf-out date. We propose that the potential to recover from frost damages is an important component of a tree's performance, particularly at the juvenile stage. The ability to recover may become even more decisive in the future with the predicted increase of false springs in many extra-tropical regions.</p>
No risk – no fun: Penalty and recovery from spring frost damages in deciduous temperate trees
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No evidence for early fitness penalty in glyphosate-resistant biotypes of Conyza canadensis: common garden experiments in the absence of glyphosate
<p>Strong selection from herbicides has led to the rapid evolution of herbicide-resistant weeds, greatly complicating weed management efforts worldwide. In particular, overreliance on glyphosate, the active ingredient in RoundUp®, has spurred the evolution of resistance to this herbicide in ≥40 species. Previously, we reported that <i>Conyza canadensis</i> (horseweed) has evolved extreme resistance to glyphosate, surviving at 40x the original 1x effective dosage. Here, we tested for underlying fitness effects of glyphosate resistance to better understand whether resistance could persist indefinitely in this self-pollinating, annual weed. We sampled seeds from a single maternal plant ("biotype") at each of 26 horseweed populations in Iowa, representing 9 susceptible biotypes (S), 8 with low-level resistance (LR), and 9 with extreme resistance (ER). In 2016 and 2017, we compared early growth rates and bolting dates of these biotypes in common garden experiments at two sites near Ames, Iowa. Nested ANOVAs showed that, as a group, ER biotypes attained similar or larger rosette size after 6 weeks compared to S or LR biotypes, which were similar to each other in size. Also, ER biotypes bolted 1-2 weeks earlier than S or LR biotypes. These fitness-related traits also varied among biotypes within the same resistance category, and time to bolting was inversely correlated with rosette size across all biotypes. Disease symptoms affected 40% of all plants in 2016 and 78% in 2017, so we did not attempt to measure lifetime fecundity. In both years, the frequency of disease symptoms was greatest in S biotypes and similar in LR vs. ER biotypes. Overall, our findings indicate there is no early growth penalty and possibly no lifetime fitness penalty associated with glyphosate resistance, including extremely strong resistance. We conclude that glyphosate resistance is likely to persist in horseweed populations, with or without continued selection pressure from exposure to glyphosate.</p>
Supporting data for ''Nonlinearity of the cloud response postpones climate penalty of mitigating air pollution in polluted regions"
<p>Supporting data for our work on Nature Climate Change. You will find:</p> <p> - python codes for generating the plots in the manuscript.</p>
Heatmap of p-values obtained by the non-parametric Wilcoxon Post-hoc Test for Experiment 1; Maximum penalty applied
<p>Heatmaps of the p-values obtained by the non-parametric Wilcoxon Post-hoc Test. </p> <p>Used for all of the following data measures across all 10 conditions. </p> <p>The maximum penalty applied for Experiment 1. </p>
No evidence for early fitness penalty in glyphosate-resistant biotypes of Conyza canadensis: common garden experiments in the absence of glyphosate
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Data from: Colonization of weakened trees by mass-attacking bark beetles: no penalty for pioneers, scattered initial distributions and final regular patterns
Bark beetles use aggregation pheromones to promote group foraging, thus increasing the chances of an individual to find a host and, when relevant, to overwhelm the defences of healthy trees. When a male beetle finds a suitable host, it releases pheromones that attract potential mates as well as other "spying" males, which results in aggregations on the new host. To date, most studies have been concerned with the use of aggregation pheromones by bark beetles to overcome the defences of living, well-protected trees. How insects behave when facing undefended or poorly defended hosts remains largely unknown. The spatio-temporal pattern of resource colonization by the European eight-toothed spruce bark beetle, Ips typographus, was quantified when weakly defended hosts (fallen trees) were attacked. In many of the replicates, colonization began with the insects rapidly scattering over the available surface and then randomly filling the gaps until a regular distribution was established, which resulted in a constant decrease in nearest-neighbour distances to a minimum below which attacks were not initiated. The scattered distribution of the first attacks suggested that the trees were only weakly defended. A minimal theoretical distance of 2.5 cm to the earlier settlers (corresponding to a density of 3.13 attacks/dm²) was calculated, but the attack density always remained lower, between 0.4 and 1.2 holes/dm², according to our observations.
The ribosome lowers the entropic penalty of protein folding
<p>This dataset contains concatenated MD trajectories for unfolded, isolated FLN5 A3A3 (iso.pdb and iso_traj.xtc) and the unfolded FLN5+31 A3A3 ribosome-nascent chain complex (RNC, nc.pdb and nc_traj.xtc). A representative structure of the ribosome model used in the simulations is also provided (ribosome_sim.pdb). Numpy array files (ending in .npy) contain the weights obtained for every frame in the ensembles after reweighting with PRE-NMR data. Text files including the trajectory frames (1-indexed, frames_nc.ndx and frames_iso.ndx) corresponding to the weights are also included (a few frames were removed because MTSL/spinlabel rotamers could not be accomdated sterically to allow for PRE calculations at protein labelling sites of interest). Both ensembles consist of ~100,000 frames. The FLN5 A3A3 ensemble was generated from ten independent MD trajectories of 2 microseconds, and FLN5+31 A3A3 consists of ten independent simulations lasting 1.5 microseconds (20 and 15 microseconds total, respectively). Independent simulations were initiated from different starting structures. The *.tar files contain initial coordinate files, MD input files and topologies. </p>
Data from: Coasting in live-bearing fish: the drag penalty of being pregnant
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Data from: Colonization of weakened trees by mass-attacking bark beetles: no penalty for pioneers, scattered initial distributions and final regular patterns
Open the record for dataset details and reuse information.
DNA mismatches reveal conformational penalties in protein-DNA recognition
GEO Series GSE156375. synthetic construct; Homo sapiens; Saccharomyces cerevisiae. 29 samples. Type: Protein profiling by protein array.
DNA mismatches reveal conformational penalties in protein-DNA recognition I
GEO Series GSE156304. synthetic construct; Saccharomyces cerevisiae; Homo sapiens. 8 samples. Type: Other.
DNA mismatches reveal conformational penalties in protein-DNA recognition IV
GEO Series GSE157065. synthetic construct. 6 samples. Type: Other.
Ef-cd locus shortens rice maturity duration without yield penalty
GEO Series GSE133746. Oryza sativa. 4 samples. Type: Expression profiling by high throughput sequencing.
DNA mismatches reveal conformational penalties in protein-DNA recognition V
GEO Series GSE157066. synthetic construct. 3 samples. Type: Other.
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